Digital signal processing (DSP) is applied to the analysis of the acoustic properties of pathological cough sounds. This work emanates from a clinical study of asthmatic, cystic fibrosis and cryptogenic fibrosing alveolitis patients. The pathological vocalisations exhibit clinically inconsistent acoustic properties from one disease to another. We aim to analyse the individual cough characteristic to adapt a DSP algorithm for identifying particular coughs and distinguishing them from background noise over long periods. The application is to obtain long-term statistical measurements to allow objective assessment of the severity of cough. This will be used for comparing the effectiveness of various treatments as well as to study the physiological characteristic of pulmonary diseases. In this work, cough identification and counting algorithm has been developed to detect and count coughs characteristic of asthma. Its accuracy has been assessed. A sensitivity of 70.5% and specificity of 98.3% were achieved.